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The First Grand Theory of Investing: Strategic Asset Allocation

You know asset allocation is kind of a big deal, are convinced it is a good idea to be diversified, and know what asset classes are out there to buy. Now it's time to figure out how much to put in each. There are two philosophies for doing so. The first is called "strategic asset allocation" (or static asset allocation), and the second is called "tactical asset allocation" or, interchangeably, "dynamic asset allocation."

In this article, we'll look at the first.

The Roots of SAA

The practical foundation of Strategic Asset Allocation (SAA) is the idea that it is impossible to "time" the markets. This idea comes from a number of academic studies. A small sample of the evidence:

A frequently-cited 1997 survey of investment newsletters conducted by two professors at Duke University found that of those that published asset allocation recommendations, only 25% were able to beat an equivalent "buy-and-hold" benchmark, suggesting that subscribers would have been better off reading the comics.

A 2002 Journal of Finance paper reports that in a study of over 65,000 individual brokerage accounts, those that traded the most earned an annual return that was 6% lower than a passive benchmark, and 5% lower than the average account in the sample.

The title of the last paper sums up the available evidence in a succinct but comprehensive six words: "trading is hazardous to your wealth."

More ardent believers in buy-and-hold would cite this as evidence that it is impossible to time the markets at all, and that anyone who tries and succeeds has merely gotten lucky. Less ardent believers may acknowledge that some traders may have the ability to time the markets for short-term gains, but argue that as a practical matter, it is very difficult for individual investors to either replicate these strategies on their own or to gain access to funds that are successful at doing so.

Instead, of timing the markets, SAA advocates a buy and hold philosophy, or perhaps more accurately a buy and re-balance philosophy. Asset allocation is set once, and then changes are only made to bring the portfolio back in to line with the initial target.

But of course in order to buy and re-balance, you have to first figure out what to buy. To answer that question, most practitioners of buy-and-hold point to something called "MPT."

Modern Portfolio Theory (MPT)

At one level, MPT is just a statement of math as it applies to the problem of combining different assets into a portfolio. MPT defines the optimal portfolio to hold as the portfolio that results in the greatest return on a risk-adjusted basis (where risk is defined as the volatility of a portfolio). It derives this portfolio from a combination of several inputs:

The expected return of each potential asset, in terms of a percentage return every year;

The expected volatility of each asset, where volatility is a measure of how much the return will "swing around" its average from year to year;

The correlations between each asset class, where correlation measures how closely the returns of different asset classes will "track" each other.

To put this in concrete terms, if you were considering a portfolio of US Stocks, European Stocks, and Treasury bonds, you could find the optimal mix of each to own by plugging in assumptions about how much each was likely to return in the future, the correlations between each pair, and an estimate of each's volatility.

The idea is that you do not just want to own the asset with the highest return, because owning just one asset would subject your portfolio to an unacceptably high level of risk. Instead, you want to own the collection of assets which best balances risks and returns, and that collection most likely includes several assets.

Another takeaway from MPT is that increasing a portfolio's returns is not the only way an investment can add value to an overall portfolio. In fact, under some circumstances, it even makes sense to own an investment that you expect to go down in value over time. If an investment has a characteristic that causes it to perform well in a time when most of the other investments in your overall portfolio are going down, it can reduce your portfolio's overall volatility dramatically.

The reason that many practitioners have adopted MPT is that so long as you are willing to accept its assumptions, it provides an "easy answer" that is grounded in some convincing-looking math. Unfortunately, more recent research has cast serious doubt on many of those assumptions...

MPT's Ugly Downside - Replacing One Set of Unknowns with Another Set of Unknowns

As a theory, MPT is instructive in that it shows us the math behind a key investing truth: owning a diversified collection of assets which are not perfectly correlated with one another can improve the risk-return tradeoff of a portfolio. If you carry this logic to its extreme, that means that there is one optimal portfolio that everyone should own, which we can calculate from expected returns, correlations, and volatilities of the set of investable assets. That much alone was probably worth the Nobel Prize that it was awarded.

The problem is that to put MPT into practice and use it to manage a real-money portfolio, there is no way immediate way to discern just what these future returns, correlations, and volatilities are. So MPT essentially replaces one set of unknowns (how much of each of these assets classes should I own?) with another set of unknowns (what are the expected future returns, risks, and pairwise correleations of investing in each of these asset classes?). It is not clear which of these sets of unknowns is actually "more unknown."

To get around this, firms which practice MPT tend to brush over this and quietly use historical data to fill in necessary assumptions. But this is clearly not quite right. For one thing, we know that the returns we expect to get on an asset should be related to the price that we are paying for it. All else equal higher prices should produce lower future returns, and vice versa. But most MPT approaches do not take this into account at all; instead they effectively assume that history will repeat itself.

The major limitation of SAA, then, is this: wanting to meet the market rather than beat it is all well and good, but it is not so easy to transfer this principle into a set of asset-class weights without over-relying on historical data. Most of the methods to construct real-world portfolios in a supposedly "prediction-free" way end up making the implicit prediction that the past is going to nearly exactly repeat itself.

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